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Today, computing magnetic resonance imaging (MRI) for brain segmentation is a major challenge in medical imaging to diagnose diseases and determine their cause in less time before the disease worsens. The proposed project aims to provide a solution through the creation of a computer-assisted method to analyse the brain MRI and CT images from research centres and hospitals. The main objective of this research work is to establish a semi-automated / full-automated scheme for detecting brain abnormalities, such as brain tumour and brain stroke, using brain images obtained with Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). This paper implies a new algorithm based on Harmony Search Optimization (HSO) and Level Set (LS) which will segment the MRI brain images automatically in a digital manner. The HSO functionality is adjusted in the proposed algorithm to automatically identify the location of the cluster of cancers as well as the number of the cluster. The level set (LS) that is derived as a tendency flow that decreases functional energy with a time of regularization. It also moves the degree of zero movements to the location of the target brain tumour, which helps doctors to determine the size and location of the brain tumours. Furthermore, evaluation of the suggested algorithm has been tested and performed using real MRI data and MATLAB software. And it can be seen from the findings of this study, which is more than 96% precision, compared to previous researchers results. By using heuristic algorithms with MATLAB software, early detection of a tumour is possible, which can save the precious human lives, and as a result, the community will be healthier and sound.
Inspec keywords: computerised tomography; cancer; image segmentation; medical image processing; tumours; brain; biomedical MRI
Subjects: Biology and medical computing; Medical magnetic resonance imaging and spectroscopy; X-rays and particle beams (medical uses); Computer vision and image processing techniques; Optical, image and video signal processing; X-ray techniques: radiography and computed tomography (biomedical imaging/measurement); Biomedical magnetic resonance imaging and spectroscopy; Patient diagnostic methods and instrumentation